Today's network environment calls for large amounts of data to be collected, aggregated, transformed, and stored in databases. New data may be received and gathered in a continuous manner or sequentially. Users of the network may request these data from relevant databases. Request results may be generated by accessing data elements in a relevant database and manipulating them in a way that yields the requested information. For example, a system may receive a large number of data elements in response to various requests. And these data elements may be fetched from various data repositories. Under certain circumstances, these data elements may need to be grouped and combined in a certain way to fulfill multiple requests. The system may need a mechanism to group and combine the data elements and return the combined data elements to relevant requestors. Conventional systems may lack a mechanism to group and combine the data elements. On the other hand, the requests themselves, may be manipulated in a way that they are properly processed to reach a desired goal. For example, the system may receive a large number of data requests from users at a given time interval (e.g., a day, an hour). The system may need to handle them in a timely fashion to meet the users' need.
Often times, a data request may request data elements of different types. For example, the data request may request a first data element comprising confidential data, and a second data element comprising public data. These different types of data elements may be stored in different data repositories, which may be located in different geographic locations. Therefore, the data request may need to be sent to multiple data repositories to fetch the data elements of different types. Conventional systems may send a data request to a first data repository to fetch a first data element, then to a second data repository to fetch a second data element. However, such sequential operation increases processing time and is not time efficient. Alternatively, conventional systems may send duplicative data requests to two data repositories. But this consumes more computing resources such as memory and bandwidth.
Furthermore, the requests and the requested information may face malicious network activities during storage and transmission over the network. Conventional systems may be unable to provide adequate network security to secure the requests and the requested information during storage and transmission over the network. As a result, these requests and the requested information may be vulnerable to attacks by malicious actors over the network.
Therefore, it is desirable to provide a solution that reduces request processing time and increases overall throughput while conserving computing resources and securing the requests and the requested information.